Aleph-Labs
Website:
aleph-labs.com
Job details:
Company Description Aleph-Labs is a creative engineering company founded in 2006, headquartered in and operating across the Asia Pacific region. The team of nearly 300 professionals collaborates across borders to design and build financial, internet, mobile, and desktop solutions for diverse clients. Aleph-Labs is known for seamlessly bridging design and technology, creating user-centric products that people enjoy using and clients are proud to own. The company emphasizes strong culture, cross-market collaboration, and practical innovation to deliver functional, flexible, and scalable solutions. Team members are encouraged to apply their unique talents, tackle complex challenges, and turn ambitious ideas into reality.
Role Description The Principal Data AI Engineer role is a full-time, hybrid position based in Mysore, with flexibility for partial work from home. This role is responsible for designing and implementing advanced AI and data solutions, including end-to-end pipelines that support machine learning models in production. Day-to-day activities include developing and optimizing algorithms, building and maintaining scalable data infrastructure, and collaborating with product, design, and engineering teams to integrate AI capabilities into customer-facing applications. The Principal Data AI Engineer will lead technical discovery, perform complex data analysis, mentor other engineers, and contribute to architectural decisions for AI and data systems. The role also involves evaluating new tools and frameworks, ensuring best practices in model performance, reliability, and security, and presenting insights and recommendations to stakeholders.
Qualifications
• Own end‑to‑end architecture and technical direction for enterprise data, analytics, ML, and GenAI systems supporting large‑scale commercial and operational use cases.
• Principal architect and technical advisor for Novo Nordisk across attribution, MMM, CEI, HCP targeting, next‑best‑action, and supply decision intelligence.
• Defined Snowflake‑centric governed data and AI platforms integrating curated data products, semantic layers, ML pipelines, and downstream decision systems.
• Established enterprise GenAI reference architectures with AI gateways for policy enforcement, auditability, model routing, and compliance.
• Designed agentic AI systems using RAG, embeddings, and bounded agents for root‑cause analysis, insight synthesis, and workflow automation.
• Led and mentored 26+ data scientists and ML engineers; set architecture standards, coding practices, and model lifecycle governance.
• Architected an ML‑driven ticket management platform adopted by 8+ internal clients, saving ~160+ hours/client/month. Strong expertise in Data Architecture and Data Modeling, with experience designing scalable and resilient data solutions.
- Hands-on experience with Extract Transform Load (ETL) processes and Data Warehousing, including modern cloud-based platforms.
- Proficiency in Data Governance, including data quality, security, compliance, and lifecycle management frameworks.
- Extensive experience in designing and implementing AI/ML-driven data solutions, including model deployment and MLOps practices.
- Advanced skills in SQL and at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java).
- Experience with cloud ecosystems (e.g., AWS, Azure, or GCP), data lake architectures, and real-time/streaming data platforms.
- Proven track record in leading architecture initiatives, influencing technical direction, and mentoring multidisciplinary teams.
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent practical experience.
- Strong communication and stakeholder management skills, with the ability to translate complex technical concepts into actionable guidance.
Click on Apply to know more.
